1. Field of the Invention
The present invention relates generally to systems and methods for information sharing and knowledge management, and more particularly for searching for and analyzing previously transmitted messages within a system for harvesting community knowledge.
2. Discussion of Background Art
Satisfying information needs in a diverse, heterogeneous information environment is challenging. In order to even approach the process of finding information resources or answers to questions, individuals typically must know either where to look, or whom to ask. This is a challenging task, especially in large enterprises where many of the members are unaware of each other's skill sets, and of all the information resources available to them.
Such challenges become ever more significant, as modern enterprises realize that their value and strength as ongoing ventures depends increasingly upon an ability of their members to easily share information. For example, individual members of an enterprise may have questions that need answered, or may need to come up to speed on particular areas of knowledge before beginning their new assignment. The enterprise itself may also need to access its strengths and weaknesses in various product, services, and research areas. Unfortunately however, meeting these information needs is often an elusive goal for many enterprises.
Current systems for storing information and/or organizational expertise include Knowledge Databases (K-bases), such as document repositories and corporate directories, and Knowledge Management systems, which rely on users to explicitly describe their personal information, knowledge, and expertise to a centralized K-base.
FIG. 1 is a dataflow diagram of a conventional knowledge management system 100. In a typical architecture, information providing users 102 explicitly decide what descriptive information they provide to a central database 104. An information seeking user 106 then performs a query on the central database 104 in order to find an information provider who perhaps may be able to answer the seeker's question.
There are several significant problems with such systems. Knowledge management systems, like that shown in FIG. 1, require that information providers spend a significant amount of time and effort entering and updating their personal information on the central database 104. For this reasons alone, such systems tend to have very low participation rates. In addition, even information providers, who take time to enter and update their information, may accidentally or purposefully misrepresent their personal information, levels of knowledge, and expertise. Furthermore, they may neglect or be unable to reveal much of their tacit knowledge. Tacit knowledge is commonly known as knowledge a user possesses, but which the user considers trivial, or may not even be consciously aware of.
Because of the inaccuracy and/or incompleteness of such personal information, information seekers, even after all of their searching efforts, may still find their questions left unanswered, perhaps because the “expert” they identified may not have the bandwidth to respond, or may have been asked same question so that they, out of frustration or boredom, stop responding.
Frequently Asked Questions (FAQ) generation within organizations is another information management problem area, which is often very time consuming and costly. As one example, most new employee's would find a FAQ list directed just to new employees very helpful. However, enterprises tend to generate such FAQs in very time consuming and inaccurate ways, such as by surveying selected employees as to what information they would have liked to know when they started work, or by just speculating as to what a new employee would perhaps want to know. As another example, an enterprise's IT department tasked with installing new hardware and/or software on the enterprise's network may be deluged with calls from all those affected. A FAQ on the installation might solve many of the problems which have arisen, however, by the time such a FAQ is created some weeks later, the installation has been completed and the problems are moot. These, however, are just two examples of FAQ generation problems. Most organizations in fact need a great number of diverse FAQs in order to operate more efficiently.
In response to the concerns discussed above, what is needed is a system and method for harvesting community knowledge that overcomes the problems of the prior art.